139 lines
5.2 KiB
Python
139 lines
5.2 KiB
Python
"""Maisaka 聊天历史视觉占位刷新器。"""
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from typing import Awaitable, Callable, Optional
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from sqlmodel import select
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from src.chat.message_receive.message import SessionMessage
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from src.common.data_models.message_component_data_model import EmojiComponent, ForwardNodeComponent, ImageComponent
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from src.common.database.database import get_db_session
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from src.common.database.database_model import Images, ImageType
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from src.common.logger import get_logger
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from .context_messages import LLMContextMessage, SessionBackedMessage
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logger = get_logger("maisaka_chat_history_visual_refresher")
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BuildHistoryMessage = Callable[[SessionMessage, str], Awaitable[Optional[LLMContextMessage]]]
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BuildVisibleText = Callable[[SessionMessage], str]
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async def refresh_chat_history_visual_placeholders(
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*,
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chat_history: list[LLMContextMessage],
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build_history_message: BuildHistoryMessage,
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build_visible_text: BuildVisibleText,
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) -> int:
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"""在进入新一轮规划前，尝试用已完成的识图结果刷新历史占位。"""
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refreshed_count = 0
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for index, history_message in enumerate(chat_history):
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if not isinstance(history_message, SessionBackedMessage):
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continue
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original_message = history_message.original_message
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if original_message is None:
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continue
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visual_components_updated = _refresh_pending_visual_components(original_message.raw_message.components)
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if visual_components_updated:
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await original_message.process(
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enable_heavy_media_analysis=False,
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enable_voice_transcription=False,
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)
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refreshed_visible_text = build_visible_text(original_message)
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if not visual_components_updated and refreshed_visible_text == history_message.visible_text:
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continue
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rebuilt_history_message = await build_history_message(original_message, history_message.source_kind)
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if rebuilt_history_message is None:
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continue
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chat_history[index] = rebuilt_history_message
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refreshed_count += 1
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return refreshed_count
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def _refresh_pending_visual_components(components: list[object]) -> bool:
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"""用缓存中的描述更新尚未补全文本的图片与表情组件。"""
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refreshed = False
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for component in components:
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if isinstance(component, ImageComponent):
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if _should_refresh_image_component(component):
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image_description = _lookup_cached_image_description(component.binary_hash)
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if image_description:
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component.content = f"[图片：{image_description}]"
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refreshed = True
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continue
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if isinstance(component, EmojiComponent):
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if _should_refresh_emoji_component(component):
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emoji_description = _lookup_cached_emoji_description(component.binary_hash)
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if emoji_description:
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component.content = f"[表情包: {emoji_description}]"
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refreshed = True
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continue
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if not isinstance(component, ForwardNodeComponent):
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continue
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for forward_component in component.forward_components:
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if _refresh_pending_visual_components(forward_component.content):
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refreshed = True
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return refreshed
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def _should_refresh_image_component(component: ImageComponent) -> bool:
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"""判断图片组件当前是否仍处于待补全文本的占位状态。"""
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return not component.content or component.content == "[图片]"
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def _should_refresh_emoji_component(component: EmojiComponent) -> bool:
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"""判断表情组件当前是否仍处于待补全文本的占位状态。"""
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return not component.content or component.content == "[表情包]"
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def _lookup_cached_image_description(image_hash: str) -> str:
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"""从数据库读取已完成的图片描述，不触发新的识图请求。"""
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if not image_hash:
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return ""
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try:
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with get_db_session() as session:
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statement = select(Images).filter_by(image_hash=image_hash, image_type=ImageType.IMAGE).limit(1)
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if image_record := session.exec(statement).first():
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if image_record.no_file_flag:
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return ""
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if image_record.vlm_processed and image_record.description:
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return str(image_record.description).strip()
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except Exception as exc:
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logger.warning(f"读取图片缓存描述失败，image_hash={image_hash}: {exc}")
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return ""
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def _lookup_cached_emoji_description(emoji_hash: str) -> str:
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"""从数据库读取已完成的表情描述，不触发新的识别请求。"""
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if not emoji_hash:
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return ""
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try:
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with get_db_session() as session:
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statement = select(Images).filter_by(image_hash=emoji_hash, image_type=ImageType.EMOJI).limit(1)
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if image_record := session.exec(statement).first():
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if image_record.no_file_flag or not image_record.description:
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return ""
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return str(image_record.description).strip()
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except Exception as exc:
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logger.warning(f"读取表情缓存描述失败，emoji_hash={emoji_hash}: {exc}")
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return ""
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